An IPv6 target generation approach based on address space forest.

Area of Science:

• Computer Networking
• Cybersecurity
• Network Scanning

Background:

• Current IPv6 target generation algorithms are limited to low-dimensional patterns, restricting efficient scanning of IPv6 network assets.
• Existing methods face challenges with uneven seed address distribution, clustering irreversibility, large-scale loss, and high-dimensional pattern spaces, hindering scalability and detectability.

Purpose of the Study:

• To propose a novel IPv6 target generation approach, 6Probe, that overcomes the limitations of existing algorithms.
• To enhance the scale and efficiency of Internet-wide IPv6 network asset scanning.
• To improve the exploration of high-dimensional pattern and loss spaces for better IPv6 address discovery.

Main Methods:

• Developed 6Probe, an IPv6 target generation approach based on an IPv6 address space forest (6ASForest).
• Constructed multiple IPv6 address space trees (6ASTrees) to form the 6ASForest.
• Leveraged seed address structure to explore high-activity regions in high-dimensional spaces.

Main Results:

• 6Probe significantly expands the scale of probed IPv6 active addresses compared to existing algorithms.
• On balanced seed sets, 6Probe probes 2.6-4.81 times more active addresses and generates 5.47-20.01 times more low-dimensional nodes than 5 typical algorithms.
• On unbalanced seed sets, 6Probe probes 137.87%-492.74% more active addresses and generates 430.81%-712.80% more low-dimensional nodes than HMap6.

Conclusions:

• The proposed 6ASForest-based 6Probe approach offers a substantial improvement in IPv6 target generation efficiency and scalability.
• 6Probe effectively addresses the limitations of low-dimensional patterns and seed address distribution in prior methods.
• This technique enables more comprehensive and efficient scanning of IPv6 network assets, crucial for Internet-wide security and management.